{
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  "metadata": {
    "colab": {
      "name": "fastquant_lesson1_accessing_pse_data.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/enzoampil/fastquant/blob/master/lessons/fastquant_lesson1_accessing_pse_data.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2HUuGnlu3af6",
        "colab_type": "text"
      },
      "source": [
        "# fastquant lesson 1\n",
        "\n",
        "## Introduction to fastquant\n",
        "**fastquant** is a python package that allows you easily access stock data from PSE Edge with as few as 2 lines of python code.\n",
        "\n",
        "Its goal is to promote data driven investments by making quantitative analysis in finance accessible to everyone.\n",
        "\n",
        "\n",
        "## Objectives and strategies\n",
        "\n",
        "1) **Raise awareness, and guide beginners** to get a sufficient foundation by teaching the basics of quant analysis with lectures presented via medium articles & online lectures\n",
        "\n",
        "2) **Make quant analysis simple and easy** w/ a high level python API that allows for lower level configuration for more advanced users - development of an easy to use python package to facilitate data driven investments\n",
        "\n",
        "|Objective|Strategy|\n",
        "|---------|--------|\n",
        "Raise awareness, and guide beginners | Tutorials via Medium articles & lectures|\n",
        "Make quant analysis simple and easy | Beginner friendly high level python API\n",
        "\n",
        "## Top down approach to lectures and package design\n",
        "\n",
        "We start w/ immediate usefulness and then work towards “deep” understanding later as more experience is gained. This approach will be reflected in the design of the blog posts, lectures, and the fastquant package.\n",
        "\n",
        "## Expect 1 - 2 lessons per month\n",
        "\n",
        "medium article + notebook -> webinar\n",
        "\n",
        "Medium article + notebook takes 1-2 weeks, while webinar will take 1-2 weeks. So the pace will generally be 1-2 webinars per month. \n",
        "\n",
        "*Webinars will be recorded and posted as content on facebook/youtube.*\n",
        "\n",
        "## Course Outline (Part 1) - Backtesting Classic Technical Analysis Indicators\n",
        "    1. Lecture 1: Accessing PSE data in 3 lines of code\n",
        "        1. Accessing PSE data in 3 lines of code\n",
        "        2. Plotting a basic SMAC strategy\n",
        "        3. The idea of backtesting\n",
        "    2. Lecture 2: Backtest your trading strategy with 5 lines of code\n",
        "    3. Lecture 3: Relative Strength Index (Intro + backtesting)\n",
        "    4. Lecture 4: Bollinger Bands (Intro + backtesting)\n",
        "    5. Lecture 5: Moving Average Convergence Divergence (Intro + backtesting)\n",
        "    6. Lecture 6: Backtesting multiple strategies at the same time\n",
        "\n",
        "## Course Outline (Part 2) [TBD] - Building Advanced Indicators w/ Statistics & Machine Learning based Approaches + other financial indicators\n",
        "\n",
        "## Setup\n",
        "    1. Let's make sure everyone gets Google Colab working\n",
        "    2. Show github and encourage people to make an account (if they want to contribute to fastquant).\n",
        "    3. Please star the repo if you find it useful! :)\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dLC0ASP1o6B8",
        "colab_type": "text"
      },
      "source": [
        "# Installation\n",
        "\n",
        "Installing `fastquant` is super simple since it's on pypi!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KLi7LnCKdure",
        "colab_type": "code",
        "outputId": "84b0a93a-70b4-498f-eb3d-a387ba997c12",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 598
        }
      },
      "source": [
        "!pip install fastquant"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: fastquant in /usr/local/lib/python3.6/dist-packages (0.1.2.5)\n",
            "Requirement already satisfied: requests-oauthlib==1.3.0 in /usr/local/lib/python3.6/dist-packages (from fastquant) (1.3.0)\n",
            "Requirement already satisfied: certifi==2019.11.28 in /usr/local/lib/python3.6/dist-packages (from fastquant) (2019.11.28)\n",
            "Requirement already satisfied: tweepy==3.8.0 in /usr/local/lib/python3.6/dist-packages (from fastquant) (3.8.0)\n",
            "Requirement already satisfied: black==19.10b0 in /usr/local/lib/python3.6/dist-packages (from fastquant) (19.10b0)\n",
            "Requirement already satisfied: requests==2.22.0 in /usr/local/lib/python3.6/dist-packages (from fastquant) (2.22.0)\n",
            "Requirement already satisfied: six==1.13.0 in /usr/local/lib/python3.6/dist-packages (from fastquant) (1.13.0)\n",
            "Requirement already satisfied: numpy==1.18.0 in /usr/local/lib/python3.6/dist-packages (from fastquant) (1.18.0)\n",
            "Requirement already satisfied: urllib3==1.25.7 in /usr/local/lib/python3.6/dist-packages (from fastquant) (1.25.7)\n",
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            "Requirement already satisfied: PySocks==1.7.1 in /usr/local/lib/python3.6/dist-packages (from fastquant) (1.7.1)\n",
            "Requirement already satisfied: backtrader==1.9.74.123 in /usr/local/lib/python3.6/dist-packages (from fastquant) (1.9.74.123)\n",
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            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib==3.1.2->fastquant) (1.1.0)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib==3.1.2->fastquant) (0.10.0)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib==3.1.2->fastquant) (2.4.6)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from kiwisolver>=1.0.1->matplotlib==3.1.2->fastquant) (42.0.2)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GHJNCDsVpD4i",
        "colab_type": "text"
      },
      "source": [
        "# Get stock data from PSE in 2 lines of code!\n",
        "\n",
        "Here I demonstrate how to get the stock data of Jollibee (JFC is the stock symbol) from January 1, 2018 to January 1, 2019.\n",
        "\n",
        "Please ensure that your date strings are in the format YYYY-MM-DD.\n",
        "\n",
        "You can find a list of company names and stock symbols [here](https://www.pesobility.com/stock/class-a)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-RoozEvNrxGn",
        "colab_type": "code",
        "outputId": "8c916cf3-f59b-4e07-f647-c7ab86102590",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        }
      },
      "source": [
        "from fastquant import get_pse_data\n",
        "df = get_pse_data('JFC', '2018-01-01', '2019-01-01')\n",
        "df.head()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Stock table exists!\n",
            "Reading stock_table.csv ...\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>open</th>\n",
              "      <th>high</th>\n",
              "      <th>low</th>\n",
              "      <th>close</th>\n",
              "      <th>value</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dt</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2018-01-03</th>\n",
              "      <td>253.4</td>\n",
              "      <td>256.8</td>\n",
              "      <td>253.0</td>\n",
              "      <td>255.4</td>\n",
              "      <td>190253754.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-04</th>\n",
              "      <td>255.4</td>\n",
              "      <td>255.4</td>\n",
              "      <td>253.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>157152856.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-05</th>\n",
              "      <td>255.6</td>\n",
              "      <td>257.4</td>\n",
              "      <td>255.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>242201952.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-08</th>\n",
              "      <td>257.4</td>\n",
              "      <td>259.0</td>\n",
              "      <td>253.4</td>\n",
              "      <td>256.0</td>\n",
              "      <td>216069242.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-09</th>\n",
              "      <td>256.0</td>\n",
              "      <td>258.0</td>\n",
              "      <td>255.0</td>\n",
              "      <td>255.8</td>\n",
              "      <td>250188588.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             open   high    low  close        value\n",
              "dt                                                 \n",
              "2018-01-03  253.4  256.8  253.0  255.4  190253754.0\n",
              "2018-01-04  255.4  255.4  253.0  255.0  157152856.0\n",
              "2018-01-05  255.6  257.4  255.0  255.0  242201952.0\n",
              "2018-01-08  257.4  259.0  253.4  256.0  216069242.0\n",
              "2018-01-09  256.0  258.0  255.0  255.8  250188588.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ow9hSTlXk7VY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "outputId": "ee1d36e0-e90c-4cda-e09e-df01e3d6d5d4"
      },
      "source": [
        "help(get_pse_data)"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Help on function get_pse_data in module fastquant.fastquant:\n",
            "\n",
            "get_pse_data(symbol, start_date, end_date, stock_table_fp='stock_table.csv', disclosures=False)\n",
            "    Returns pricing data for a specified stock.\n",
            "    \n",
            "    Parameters\n",
            "    ----------\n",
            "    symbol : str\n",
            "        Symbol of the stock in the PSE. You can refer to this link: https://www.pesobility.com/stock.\n",
            "    start_date : str\n",
            "        Starting date (YYYY-MM-DD) of the period that you want to get data on\n",
            "    end_date : str\n",
            "        Ending date (YYYY-MM-DD) of the period you want to get data on\n",
            "    stock_table_fp : str\n",
            "        File path of an existing stock table or where a newly downloaded table should be saved\n",
            "    \n",
            "    Returns\n",
            "    -------\n",
            "    pandas.DataFrame\n",
            "        Stock data (in OHLCV format) for the specified company and date range\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t3J0y8tApNPg",
        "colab_type": "text"
      },
      "source": [
        "# Plot daily closing prices\n",
        "\n",
        "For this part, we'll want to import a plotting package, matplotlib, to be able to visualize the closing prices of Jollibee. Don't worry if you don't understand how this works - for now, just take the code as is."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_kyvYm6LsOAu",
        "colab_type": "code",
        "outputId": "bf969eff-ea7b-4b08-f94c-8e21cb20bc70",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        }
      },
      "source": [
        "from matplotlib import pyplot as plt\n",
        "df.close.plot(figsize=(10, 6))\n",
        "plt.title(\"Daily Closing Prices of JFC\\nfrom 2018-01-01 to 2019-01-01\", fontsize=20)"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Daily Closing Prices of JFC\\nfrom 2018-01-01 to 2019-01-01')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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btmPcvQ7lmNvfuTEj2NYfn3fPo275J4p8rwuxWV0G+BPwBeBX7nU3cLzPNk+49cNu3gb4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\nQyITqyRJkiRJkiHxP6M4TuvCE2ICAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "reBMiCPipO8O",
        "colab_type": "text"
      },
      "source": [
        "# Analyze with a simple moving average crossover (SMAC) trading strategy\n",
        "\n",
        "Now that we have the data ready, let's visualize a sample SMAC strategy."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M0N_DVop_q9l",
        "colab_type": "text"
      },
      "source": [
        "First, let's import the pandas library (general purpose library for handling tabular data)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MFh05xKi__jE",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mWCoJMg0AEeJ",
        "colab_type": "text"
      },
      "source": [
        "Next, we calculate the 30 day moving average of Jollibee's closing price and combine it with the original closing price data."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OzGM50VJ__nS",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "ma30 = df.close.rolling(30).mean()\n",
        "close_ma30 = pd.concat([df.close, ma30], axis=1).dropna()\n",
        "close_ma30.columns = ['Closing Price', 'Simple Moving Average (30 day)']"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sKn5XutJgMCH",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "850759da-c482-4ce6-b484-88e1b8b174cd"
      },
      "source": [
        "ma30.dropna()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dt\n",
              "2018-02-13    276.586667\n",
              "2018-02-14    277.340000\n",
              "2018-02-15    278.340000\n",
              "2018-02-19    279.340000\n",
              "2018-02-20    280.340000\n",
              "                 ...    \n",
              "2018-12-20    287.446667\n",
              "2018-12-21    288.193333\n",
              "2018-12-26    288.660000\n",
              "2018-12-27    289.360000\n",
              "2018-12-28    289.993333\n",
              "Name: close, Length: 214, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XkDyl5VlgX-V",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392
        },
        "outputId": "e10faeb9-92da-47da-ff4b-934b5b0515f8"
      },
      "source": [
        "ma30.dropna().plot(figsize=(10, 6))"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f639ebea668>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Ebv/LNu57p1hnCoqIyMd6fU8tS3MTiXFzz0q/LKz6Blw8s6WCC+emawegj4gMDeLhz5/C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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Am98ewgDAIEq",
        "colab_type": "text"
      },
      "source": [
        "Lastly, we plot the trends for the daily crossing prices and the 30 day SMA together"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5UNQLarRs7Uv",
        "colab_type": "code",
        "outputId": "eab889b6-ba24-4584-eaff-a45c89c23c1f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        }
      },
      "source": [
        "close_ma30.plot(figsize=(10, 6))\n",
        "plt.title(\"Daily Closing Prices vs 30 day SMA of JFC\\nfrom 2018-01-01 to 2019-01-01\", fontsize=20)"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Daily Closing Prices vs 30 day SMA of JFC\\nfrom 2018-01-01 to 2019-01-01')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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d2FAT3hgqXF+xfA7702gpSh/UFKhsL0QLIR7eA21cnPLxUfUGHREJYE2SZ2Jj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pUBZVneDTwF7AFeB26XZXkU52WoqKgMRGm2FW9odl1v9tSK4bGnFKaHtR6eRGmsFOZeLea6bXsk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\n5JSn/KRXAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L_IVdK9vCfox",
        "colab_type": "text"
      },
      "source": [
        "## Bonus: Get company disclosures"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q3hEimZIo0dO",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from fastquant import get_company_disclosures"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H_8dkab7DvLj",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "jfc_disclosures = get_company_disclosures('JFC', from_date='06-26-2018', to_date='06-26-2019')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lQuVJs6n2CtD",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "outputId": "2db763c1-7015-4483-e60b-5f2900636083"
      },
      "source": [
        "help(get_company_disclosures)"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Help on function get_company_disclosures in module fastquant.fastquant:\n",
            "\n",
            "get_company_disclosures(symbol, from_date='06-26-2017', to_date='06-26-2019')\n",
            "    symbol str - Ticker of the pse stock of choice\n",
            "    from_date date str %m-%d-%Y - Beginning date of the disclosure data pull\n",
            "    to_date date str %m-%d-%Y - Ending date of the disclosure data pull\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hEaBvdk7DxkR",
        "colab_type": "code",
        "outputId": "60b4caf1-22b7-486b-b575-381553726668",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        }
      },
      "source": [
        "jfc_disclosures.iloc[0]"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Company Name                                     Jollibee Foods Corporation\n",
              "Template Name             [Amend-2]Notice of Annual or Special Stockhold...\n",
              "PSE Form Number                                                         7-1\n",
              "Announce Date and Time                                  2019-05-29 11:41:00\n",
              "Circular Number                                                 C03719-2019\n",
              "edge_no                                    8a9a820ee365687cefdfc15ec263a54d\n",
              "url                       https://edge.pse.com.ph/openDiscViewer.do?edge...\n",
              "Name: 1, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0oRX5ZtkjATI",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "3d329dec-a90e-4a4b-c0ae-e6b094fa7005"
      },
      "source": [
        "jfc_disclosures.iloc[0].url"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'https://edge.pse.com.ph/openDiscViewer.do?edge_no=8a9a820ee365687cefdfc15ec263a54d'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vk8Igdzm2Qk5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "34ae8762-333c-4279-c9ff-8ba6b1c7470e"
      },
      "source": [
        "jfc_disclosures.iloc[15]['Template Name']"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'[Amend-1]Amendments to By-Laws'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TCjMVu7nAb5_",
        "colab_type": "text"
      },
      "source": [
        "Question: how can we apply a sentiment analysis to company disclosures?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2FJLYWEEAnSr",
        "colab_type": "text"
      },
      "source": [
        "## Relevant resources\n",
        "1. [Access Philippine Stock Data with Only 2 Lines of Python](https://towardsdatascience.com/access-philippine-stock-data-with-only-2-lines-of-python-309780382b8d?source=friends_link&sk=d4eab964eae7407a62690e4be1c165d7)\n",
        "2. [Technical analysis basics from investopedia](https://www.investopedia.com/technical-analysis-basic-education-4689655)\n",
        "3. [My Learning Plan for Getting Into Data Science from Scratch](https://towardsdatascience.com/my-learning-plan-for-getting-into-data-science-from-scratch-9562f37b4dde?source=friends_link&sk=b67ab491956a074123b4260df1667de4)\n",
        "\n",
        "## Thank you!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jemum_6vjv61",
        "colab_type": "text"
      },
      "source": [
        "Rafael - can contribute to 1) refactoring, 2) sentiment analysis on content"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w_pSsoQAAgbE",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}